This invention relates generally to systems and methods for controlling a process system and more particularly, to implementing model predictive control (MPC) in a real time controller.
Model predictive control typically is used to determine an optimum control output profile based on the results of a model of the process involved. The model predicts the future outcome of control output changes. This technique is particularly useful when the process involved is complex or has a long time constant. One such application is steam turbine rotor stress and axial clearance control. The effects of some control outputs, such as, turbine load on steam turbine rotor stress are not realized for 30 minutes or more. A standard approach to model predictive control involves extensive linear algebraic manipulation. The size of the computing problem is driven by several factors: prediction horizon (time), control step size, and number of model states. The resulting control profile can be complex, changing in value over the prediction horizon as needed to produce an optimal solution. Accordingly, implementing MPC using traditional techniques in existing control systems is not possible due to the large computational effort required.